Load Management of Modular Battery Using Model Predictive Control: Thermal and State-of-Charge Balancing

Altaf, Faisal; Egardt, Bo; Mårdh, Lars Johannesson

doi:10.1109/tcst.2016.2547980

Cited by 81 publications

(47 citation statements)

References 29 publications

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“…The shape of the piecewise linear optimized model is more regular and smooth with respect to the data derived by the extraction procedure. The internal resistances R i , R 1 , and R 2 increase with the temperature, as has been shown in other works [14,38]. The increment of the resistances in conjunction with the reduction of OCV causes the well-known effect of reduced battery efficiency at low temperature.…”

Section: Results: Single Cell Characterizationsupporting

confidence: 65%

Lithium-ion Battery Electrothermal Model, Parameter Estimation, and Simulation Environment

et al. 2017

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Abstract:The market for lithium-ion batteries is growing exponentially. The performance of battery cells is growing due to improving production technology, but market request is growing even more rapidly. Modeling and characterization of single cells and an efficient simulation environment is fundamental for the development of an efficient battery management system. The present work is devoted to defining a novel lumped electrothermal circuit of a single battery cell, the extraction procedure of the parameters of the single cell from experiments, and a simulation environment in SystemC-WMS for the simulation of a battery pack. The electrothermal model of the cell was validated against experimental measurements obtained in a climatic chamber. The model is then used to simulate a 48-cell battery, allowing statistical variations among parameters. The different behaviors of the cells in terms of state of charge, current, voltage, or heat flow rate can be observed in the results of the simulation environment.

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Section: Results: Single Cell Characterizationsupporting

confidence: 65%

Lithium-ion Battery Electrothermal Model, Parameter Estimation, and Simulation Environment

et al. 2017

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“…The modular battery system based on cascaded converters is a potential candidate for simultaneous thermal and SOC balancing purpose [12]- [14], [16], [17]. The modular battery consists of n cascaded power units (PUs), each containing a smaller battery module and a dc/dc converter, which enables bidirectional power flow from each module.…”

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confidence: 99%

“…The concept of modular battery is also studied recently by other authors for xEVs [18]- [21] as well as for smart grid energy storage applications [22], but only SOC balancing and voltage control problems are addressed at most. The modular battery proposed in our earlier studies [16], [17] targets multiple control objectives including thermal balancing, SOC balancing, and dclink voltage regulation. This requires a more advanced control algorithm to decide power flow from each module.…”

mentioning

confidence: 99%

“…The electro-thermal control problem of the modular battery can be solved using a one-step model predictive control (MPC) scheme, which requires information only about current battery power demand [16], [17]. The problem is formulated on a standard linear quadratic (LQ) form based on the decomposition of controller into two orthogonal components, one for voltage control and the other for balancing control.…”

mentioning

confidence: 99%

“…Therefore, the balancing controller corrects the power distribution by optimally exploiting the available redundancy in the modular battery to achieve thermal and SOC balancing without disturbing the voltage. However, the studies [16] and [17] were restricted to unipolar control (UPC) of modular battery. The UPC mode only needs a half-bridge converter with single unipolar pulse-width modulation (PWM) in each module, but it does not allow polarity inversion of battery cells.…”

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Comparative Analysis of Unipolar and Bipolar Control of Modular Battery for Thermal and State-of-Charge Balancing

Altaf

Egardt

2017

IEEE Trans. Veh. Technol.

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Thermal and state-of-charge imbalance is a well known issue to cause nonuniform ageing in batteries. The modular battery based on cascaded converters is a potential solution to this problem. This paper presents bipolar control (BPC) of a modular battery and compares it with previously proposed unipolar control (UPC) mode in terms of thermal/SOC balancing performance and energy efficiency. The BPC needs four-quadrant operation of full-bridge converter using bipolar pulse-width modulation (PWM) inside each module, whereas UPC only needs half-bridge converter with unipolar PWM. The BPC, unlike UPC, enables charging of some cells while discharging others. An averaged state-space electro-thermal battery model is derived for a convex formulation of the balancing control problem. The control problem is formulated on a constrained LQ form and solved in a model predictive control framework using one-step ahead prediction. The simulation results show that BPC, without even requiring load current variations, gives better balancing performance than UPC, but at the cost of reduced efficiency. The UPC requires at least current direction reversal for acceptable balancing performance. In short, the UPC is a more cost and energy efficient solution for EV and PHEV applications whereas the BPC can be beneficial in applications involving load cycles with high current pulses of long duration. Index Terms-Modular battery, SOC balancing, thermal balancing, multilevel converters, averaging, model predictive control. I. INTRODUCTION The electrification and hybridization of vehicle powertrain is being vastly adopted by automotive industry to increase fuel efficiency and to meet ever decreasing exhaust emission limits. The Lithium-ion battery is one of the major alternative power sources currently being considered for this purpose. The battery pack of these electrified/hybridized vehicles (xEVs) is one of the most expensive, but a key component in the powertrain. Therefore, the battery lifetime is an important factor for the success of xEVs. The conventional battery system in xEVs consists of long string of series connected modules along with dc/dc converter for dc-link voltage regulation as shown in Fig. 1. Due to the fixed series connection, the same current passes through all the modules. This is a socalled uniform duty operation (UDO) of cells. If modules have nonuniform state-of-health (parametric variations) then they may suffer from unequal stress and energy drain under

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A finite‐state machine‐based control design for thermal and state‐of‐charge balancing of lithium iron phosphate battery using flyback converters

Zabetian‐Hosseini,

Ghazanfari,

Boulet

2024

Battery Energy

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Battery cell balancing plays a vital role in maximizing the performance of the battery system by enhancing battery system capacity and prolonging the battery system life expectancy. Active cell balancing using power converters is a promising approach to maintaining uniform state of charges (SoCs) and temperatures across battery cells. The SoC balancing function in the battery management system (BMS) increases the battery pack capacity, and the temperature balancing function mitigates variations in the aging of battery cells due to unbalanced temperatures. In this work, a finite‐state machine‐based control design is proposed for lithium iron phosphate (LFP) battery cells in series to balance SoCs and temperatures using flyback converters. The primary objective of this design is to ensure balanced SoCs by the end of the charging session while mitigating the temperature imbalance during the charging process. To achieve the SoC and temperature balancing functions using the same balancing circuits, a finite‐state machine control design decides on the operating mode, and a balancing strategy balances either temperature or SoC depending on the operating mode. The proposed control design has the advantages of low computational burden, simple implementation compared to the optimization‐based controller found in the literature, and the proposed balancing strategy offers faster balancing speed compared to conventional methods. The effectiveness of the proposed strategy is validated on battery cell RC models in series with unbalanced SoCs and temperatures.

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Load Management of Modular Battery Using Model Predictive Control: Thermal and State-of-Charge Balancing

Cited by 81 publications

References 29 publications

Lithium-ion Battery Electrothermal Model, Parameter Estimation, and Simulation Environment

Lithium-ion Battery Electrothermal Model, Parameter Estimation, and Simulation Environment

Comparative Analysis of Unipolar and Bipolar Control of Modular Battery for Thermal and State-of-Charge Balancing

A finite‐state machine‐based control design for thermal and state‐of‐charge balancing of lithium iron phosphate battery using flyback converters

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